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Aisuite
Overview :
aisuite is a product that provides a simple, unified interface to access multiple generative AI services. It enables developers to use multiple large language models (LLMs) through a standardized interface and compare results. As a lightweight Python client library wrapper, aisuite allows creators to seamlessly switch and test responses from different LLM providers without altering the code. Currently, the library mainly focuses on chat completion features and plans to expand to more use cases in the future.
Target Users :
The target audience consists of developers and data scientists, particularly those professionals who need to switch and test between different LLMs to achieve the best results. The unified interface and ease of use offered by aisuite allow these users to conduct model testing and integration more efficiently, without needing to delve deeply into the specific API details of each provider.
Use Cases
Generate responses for a chatbot using aisuite.
Compare answers from different LLM providers on the same question.
Integrate into existing chat applications to provide richer conversational features.
Features
Supports multiple LLM providers: including OpenAI, Anthropic, Azure, Google, AWS, etc.
Unified interface: Makes switching between different models simple by using the <provider>:<model-name> format.
Easy installation: Can be installed via pip, either the base package or a package that includes specific provider SDKs.
Environment variable or configuration passing: Supports setting API keys as environment variables or passing them directly to the Client constructor.
Rich code examples: Provides multiple examples to help users quickly get started and experiment with the interface.
MIT License: Allows free use, modification, and distribution of the code for both commercial and non-commercial purposes.
Community contributions: Encourages developers to support new platforms by adding implementation files to collectively expand functionality.
How to Use
1. Install the aisuite library: Run `pip install aisuite` in the command line.
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2. Obtain API keys: Acquire API keys from various LLM providers.
3. Set up API keys: Configure API keys as environment variables or pass them directly to the Client in code.
4. Write code: Use the interfaces provided by aisuite to write code that calls different LLM models.
5. Run and test: Execute your code and test the responses of different models, comparing the results.
6. Adjust parameters: Modify model parameters, such as temperature, as needed to optimize output.
7. Integrate into applications: Incorporate the tested code into actual applications or services.
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